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AI Tools Usage

Analyze how developers use AI coding tools like GitHub Copilot and Cursor. This view surfaces active users, acceptance rates, and code contribution trends so you can evaluate trust, engagement, and real productivity impact across teams.

Steven Silverstone
Updated by Steven Silverstone

The AI Tools Usage panel measures how developers use supported AI coding tools across your organization. LinearB currently supports GitHub Copilot, Cursor, and Claude.

Note The AI Tool Usage views in AI Insights, along with the standalone Copilot and Cursor dashboards, will be deprecated on April 2nd 2026.

These dashboards relied on third-party API data that may include contributors outside your LinearB team scope, which can lead to inconsistent reporting and limited filtering capabilities.

For accurate, filterable, and team-scoped insights, use the AI Analytics dashboards.

Chatbot and bot accounts are excluded from all metrics.

Overview

  • Track AI tool adoption and usage across developers.
  • Measure trust and value using acceptance and trend metrics.
  • Use drilldowns (where available) to move from percentages to underlying counts.

What the panel measures

For each supported tool, the panel provides the following metrics:

  • Active users – Number of developers actively using the tool. Measured by counting developers who accept AI code suggestions, use AI chat, or trigger AI-powered PR summaries. Authentication-only events are excluded.
Note on grouping: Active Users may appear different depending on how data is grouped:
  • Grouped by Team – shows the average number of active users per interval over the selected time range.
  • Grouped by User – shows individual user activity.

For example, if 4 users are active on different days, the Team view may show about 2.8 active users per day on average, while the User view shows all 4 users individually. Both views reflect the same underlying data, but use different aggregation methods.

Note on counting: A single user can be counted as active more than once per day if they use multiple AI tools.

For example, if a developer uses both GitHub Copilot and Cursor on the same day, they may be counted once for each tool in aggregated views.

  • Acceptance rate – Percentage of AI suggestions accepted into code. Measured by comparing suggestions offered vs. suggestions accepted.
  • Code acceptance – A trend chart showing accepted AI-generated code over time. Measured by grouping accepted AI-generated code by day.
GitHub Copilot

LinearB tracks GitHub Copilot using GitHub’s official Usage API.

Experiencing a 403 Unauthorized error, adoption above 100%, or missing user-level data? See GitHub Copilot Troubleshooting .

Organization-level Copilot metrics may appear in AI Insights even if no users are shown as connected in the Users page. User-level visibility depends on Copilot usage metrics being enabled in GitHub and successful GitHub-to-LinearB identity mapping.

How did we do?

AI Tools Integrations

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